Title :
Navigating heterogeneous processors with market mechanisms
Author :
Guevara, M. ; Lubin, B. ; Lee, Brian C.
Abstract :
Specialization of datacenter resources brings performance and energy improvements in response to the growing scale and diversity of cloud applications. Yet heterogeneous hardware adds complexity and volatility to latency-sensitive applications. A resource allocation mechanism that leverages architectural principles can overcome both of these obstacles. We integrate research in heterogeneous architectures with recent advances in multi-agent systems. Embedding architectural insight into proxies that bid on behalf of applications, a market effectively allocates hardware to applications with diverse preferences and valuations. Exploring a space of heterogeneous datacenter configurations, which mix server-class Xeon and mobile-class Atom processors, we find an optimal heterogeneous balance that improves both welfare and energy-efficiency. We further design and evaluate twelve design points along the Xeon-to-Atom spectrum, and find that a mix of three processor architectures achieves a 12× reduction in response time violations relative to equal-power homogeneous systems.
Keywords :
cloud computing; computer centres; microprocessor chips; multi-agent systems; power aware computing; resource allocation; cloud applications; data center configurations; datacenter resources; energy improvements; market mechanisms; mobile class Atom processors; multiagent systems; navigating heterogeneous processors; performance improvements; resource allocation mechanism; server class Xeon processors; Computer architecture; Hardware; Mathematical model; Microarchitecture; Program processors; Resource management; Servers;
Conference_Titel :
High Performance Computer Architecture (HPCA2013), 2013 IEEE 19th International Symposium on
Conference_Location :
Shenzhen
Print_ISBN :
978-1-4673-5585-8
DOI :
10.1109/HPCA.2013.6522310